Statistical Methods for Reliability Data - (Wiley Probability and Statistics) 2nd Edition by William Q Meeker & Luis A Escobar & Francis G Pascual

About the Book

"This book improves Meeker and Escobar (1998, Wiley) not only in terms of organization and presentation, but also in extensions and modifications to the technical material. It presents state-of-the-art, computer-based statistical methods for reliability data analysis and for test planning of industrial products. It also improves long time established techniques as it demonstrates how to apply the new graphical, numerical, or simulation-based methods to a broad range of models encountered in reliability data analysis. Bayesian methods in solving practical problems (e.g. models involving random effects or censoring that arises in reliability studies) are now incorporated where appropriate; the computations are done with WinBUGS. Ample exercises that extend and strengthen the concepts in the book are included. The criterion for integrating material in the book is that the authors have in-hand or have seen real applications for the methodology. The book is specifically geared for a one-semester course on the topic in either a statistics or engineering department at either the upper-undergraduate or beginning graduate levels. R functions and subroutines, along with an extensive list of data sets, are included on a massive web site that is meticulously maintained by the authors"--

Book Synopsis

An authoritative guide to the most recent advances in statistical methods for quantifying reliability

Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book's website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook.

The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data.

SMRD2 features:

• Contains a wealth of information on modern methods and techniques for reliability data analysis
• Offers discussions on the practical problem-solving power of various Bayesian inference methods
• Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website
• Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter
• Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts

Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.

From the Back Cover

An authoritative guide to the most recent advances in statistical methods for quantifying reliability

Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book's website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook.

The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data.

SMRD2 features:

• Contains a wealth of information on modern methods and techniques for reliability data analysis
• Offers discussions on the practical problem-solving power of various Bayesian inference methods
• Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website
• Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter
• Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts

Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.

About the Author

William Q. Meeker, PhD, is Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He is a Fellow of the American Association for the Advancement of Science, the American Statistical Association, and the American Society for Quality.

Luis A. Escobar, PhD, is a Professor in the Department of Experimental Statistics at Louisiana State University. He is a Fellow of the American Statistical Association, an elected member of the International Statistics Institute, and an elected Member of the Colombian Academy of Sciences.

Francis G. Pascual, PhD, is an Associate Professor in the Department of Mathematics and Statistics at Washington State University.